Compression of unfocused plenoptic images using a displacement intra prediction

Plenoptic images are one type of light field contents produced by using a combination of a conventional camera and an additional optical component in the form of microlens arrays, which are positioned in front of the image sensor surface. This camera setup can capture a sub-sampling of the light field with high spatial fidelity over a small range, and with a more coarsely sampled angle range. The earliest applications that leverage on the plenoptic image content is image refocusing, non-linear distribution of out-of-focus areas, SNR vs. resolution trade-offs, and 3D-image creation. All functionalities are provided by using post-processing methods. In this work, we evaluate a compression method that we previously proposed for a different type of plenoptic image (focused or plenoptic camera 2.0 contents) than the unfocused or plenoptic camera 1.0 that is used in this Grand Challenge. The method is an extension of the state-of-the-art video compression standard HEVC where we have brought the capability of bi-directional inter-frame prediction into the spatial prediction. The method is evaluated according to the scheme set out by the Grand Challenge, and the results show a high compression efficiency compared with JPEG, i.e., up to 6 dB improvements for the tested images.